Architect

Summary

Join Tiger Analytics, a rapidly expanding advanced analytics consulting firm, as a Databricks Architect. You will be responsible for designing and implementing best data practices, leveraging your expertise in Databricks Lakehouse, AWS, Snowflake, and Apache Iceberg. This role demands strong MLOps & CI/CD expertise and proficiency in Python/Scala (Spark). You will architect and strategize Databricks on AWS/Snowflake integration, design cost-managed multi-region Databricks MLOps platforms, and implement Unity Catalog for secure access control. The position offers significant career development opportunities in a challenging and entrepreneurial environment. Remote work is possible.

Requirements

• Strong Experience in Data Architecture, specifically with Databricks Architecture
• Expert in Databricks Lakehouse (Delta Lake, Unity Catalog, MLflow), AWS, Snowflake, and Apache Iceberg
• Strong MLOps & CI/CD Expertise
• Proficient in Python/Scala (Spark) for data governance, security, and enterprise data platform design

Responsibilities

• Architect and strategize Databricks on AWS/Snowflake integration for secure, scalable data/AI platforms
• Architect seamless Snowflake/Databricks data flow via Apache Iceberg (including ML output)
• Design cost-managed multi-region Databricks MLOps platform and data flows
• Implement Unity Catalog for fine-grained access control and secure team coexistence with Workspaces
• Develop Databricks-native MLOps (environment parity, Git-driven CI/CD, governed access, MLflow governance, standardized deployment, monitoring)
• Define enterprise-scalable AI governance for GenAI production deployment

Preferred Qualifications

Databricks certifications and GenAI architecture experience